Least Overhead Ingestion to OpenSearch via Kinesis

Automate data processing by using AWS services.

Answer Correct answer: A — Use Amazon Kinesis Data Firehose and an AWS Lambda function to transform the data and deliver the transformed data to OpenSearch Service.

A media company wants to use Amazon OpenSearch Service to analyze rea-time data about popular musical artists and songs. The company expects to ingest millions of new data events every day. The new data events will arrive through an Amazon Kinesis data stream. The company must transform the data and then ingest the data into the OpenSearch Service domain. Which method should the company use to ingest the data with the LEAST operational overhead?

Use Amazon Kinesis Data Firehose and an AWS Lambda function to transform the data and deliver the transformed data to OpenSearch Service. Correct Answer
Use a Logstash pipeline that has prebuilt filters to transform the data and deliver the transformed data to OpenSearch Service.
Use an AWS Lambda function to call the Amazon Kinesis Agent to transform the data and deliver the transformed data OpenSearch Service.
Use the Kinesis Client Library (KCL) to transform the data and deliver the transformed data to OpenSearch Service.

Community Votes

50%

50% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.

Community Insight

The core concept is choosing a fully managed service (Firehose) over self-managed components (Logstash, KCL) to minimize infrastructure management tasks.

This question evaluates the optimal AWS architecture for streaming data ingestion with minimal operational overhead. The correct solution leverages Amazon Kinesis Data Firehose combined with an AWS Lambda function to handle transformation and delivery to Amazon OpenSearch Service.

Many candidates choose Logstash (Option B) because it is commonly associated with the ELK stack for Elasticsearch/OpenSearch, failing to recognize that managing Logstash instances requires significantly more operational effort than using the managed Firehose service.

Community Discussion (5 comments)

Evan_Lin 👍 2 Selected: B

why not B? Logstash is an open-source data ingestion tool that allows you to collect data from various sources, transform it, and send it to your desired destination. With prebuilt filters and support for over 200 plugins, Logstash allows users to easily ingest data regardless of the data source or type.

maddyr 👍 2 Selected: B

Logstash is a lightweight, open-source, server-side data processing pipeline that allows you to collect data from various sources, transform it on the fly, and send it to your desired destination. It is most often used as a data pipeline for Elasticsearch, an open-source analytics and search engine https://aws.amazon.com/what-is/elk-stack/#seo-faq-pairs#what-is-the-elk-stack

mzansikiller 👍 1

Amazon Kinesis Data Firehose is a fully managed service that reliably loads streaming data into data lakes, data stores and analytics services like OpenSearch Service. It can automatically scale to match the throughput of your data and requires no ongoing administration. Answer A

aragon_saa 👍 1 Selected: A

Answer is A

matt200 👍 3 Selected: A

Option A: Use Amazon Kinesis Data Firehose and an AWS Lambda function to transform the data and deliver the transformed data to OpenSearch Service is the best choice for achieving the least operational overhead. Kinesis Data Firehose is a managed service that automates the data ingestion process, scales seamlessly, and integrates directly with OpenSearch Service, minimizing the need for manual intervention and infrastructure management.

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Expert Analysis

Why the Answer Is Correct

Amazon Kinesis Data Firehose is a fully managed service designed specifically for loading streaming data into AWS destinations like S3, Redshift, Splunk, and OpenSearch. It automatically scales to match the throughput of your data and requires no ongoing administration. By attaching an AWS Lambda function to Firehose, you can perform real-time data transformation before delivery. This combination offers the least operational overhead because AWS manages the underlying servers, scaling, and error handling.

Why the Other Options Are Wrong

Option B (Logstash) is a powerful open-source tool, but running Logstash pipelines typically requires provisioning and managing EC2 instances or Kubernetes clusters, which introduces significant operational overhead compared to the serverless nature of Firehose. Option C is incorrect because the Kinesis Agent is primarily used for log shipping from on-premises or EC2 sources to Kinesis Streams/Delivery Streams, not as a transform-and-deliver mechanism in this context, and calling it via Lambda is architecturally unsound. Option D (Kinesis Client Library) requires developers to build and maintain their own consumer applications to process records, resulting in high operational overhead and complexity.

Community Comment Notes

Community feedback was split between A and B. Some users argued for Logstash due to its familiarity in the ELK ecosystem, as seen in comments discussing prebuilt filters. However, others correctly identified Firehose as the superior choice for 'least operational overhead' because it is a managed service. One commenter noted that Firehose 'automatically scale[s] to match the throughput... and requires no ongoing administration,' which directly addresses the exam's constraint.

Exam Strategy

When an exam question asks for the 'LEAST operational overhead' involving data ingestion and transformation, prioritize fully managed AWS services (like Firehose, Glue, Lambda) over self-managed tools (like Logstash, EMR, or custom code). Always compare the management burden of the infrastructure required for each option.

Frequently Asked Questions

Why is Logstash not the best choice for least overhead?

Logstash is open-source and typically requires managing EC2 instances or clusters to run, whereas Kinesis Data Firehose is a fully managed service that handles scaling and maintenance automatically.

Can I use Lambda alone without Firehose?

You can use Lambda to process Kinesis streams, but integrating it directly with OpenSearch often requires custom code for batching and retry logic. Firehose provides built-in buffering, compression, and retry mechanisms, reducing overhead.

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